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Enhancing anomaly detection in satellite imagery using self-supervised learning techniques.

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Title: Enhancing anomaly detection in satellite imagery using self-supervised learning techniques.
Authors: Barba-Rojas, Raúl1, raul.barba@ubotica.com, Espinosa-Aranda, Jose Luis1, josel.espinosa@ubotica.com, Díez, Jorge2, jdiez@uniovi.es
Source: Neural Computing & Applications; Jan2026, Vol. 38 Issue 2, p1-22, 22p
Database: Applied Science & Technology Source
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  Availability: 0
Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 191134281
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Enhancing anomaly detection in satellite imagery using self-supervised learning techniques.
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=191134281
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1007/s00521-025-11746-w
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      – Code: eng
        Text: English
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        PageCount: 22
        StartPage: 1
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      – TitleFull: Enhancing anomaly detection in satellite imagery using self-supervised learning techniques.
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            NameFull: Barba-Rojas, Raúl
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            NameFull: Espinosa-Aranda, Jose Luis
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            NameFull: Díez, Jorge
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              Text: Jan2026
              Type: published
              Y: 2026
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              Value: 38
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            – TitleFull: Neural Computing & Applications
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